A modified Chimpanzee Algorithm(CGChOA)is proposed to address the issues of uneven initial population distri-bution,poor individual adaptability,and susceptibility to local optima that arise during the optimization process of the standard Chimpanzee optimization algorithm.Firstly,using chaotic Cat mapping to generate the initial position of the chimpanzee population to enrich population diversity;Secondly,a convergence factor based on the cosine variation law is introduced to balance the global exploration and local development capabilities of the algorithm;Finally,Gaussian mutation is performed on the individuals of chim-panzees at the best search location to avoid the algorithm falling into local optima.The superiority of our algorithm was verified through comparative experiments of 10 benchmark test functions and 2 engineering application problems.
关键词
黑猩猩优化算法/Cat映射/收敛因子/高斯变异/优胜劣汰
Key words
Chimpanzee optimization algorithm/Cat mapping/convergence factor/Gaussian variation/survival of the fittest
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